add fixture

This commit is contained in:
Peter Baumgartner 2023-01-24 14:06:56 -05:00
parent 17c4bfc181
commit e4183ca354

View File

@ -120,24 +120,23 @@ def test_benchmark_accuracy_alias():
), ),
], ],
) )
def test_init_config_trainable(component, examples): def test_init_config_trainable(component, examples, en_vocab):
nlp = English()
if component == "textcat": if component == "textcat":
train_docs = [] train_docs = []
for example in examples: for example in examples:
doc = Doc(nlp.vocab, words=example["words"]) doc = Doc(en_vocab, words=example["words"])
doc.cats = example["cats"] doc.cats = example["cats"]
train_docs.append(doc) train_docs.append(doc)
elif component == "spancat": elif component == "spancat":
train_docs = [] train_docs = []
for example in examples: for example in examples:
doc = Doc(nlp.vocab, words=example["words"]) doc = Doc(en_vocab, words=example["words"])
doc.spans["sc"] = [ doc.spans["sc"] = [
Span(doc, start, end, label) for start, end, label in example["spans"] Span(doc, start, end, label) for start, end, label in example["spans"]
] ]
train_docs.append(doc) train_docs.append(doc)
else: else:
train_docs = [Doc(nlp.vocab, **example) for example in examples] train_docs = [Doc(en_vocab, **example) for example in examples]
with make_tempdir() as d_in: with make_tempdir() as d_in:
train_bin = DocBin(docs=train_docs) train_bin = DocBin(docs=train_docs)